Observatorio de I+D+i UPM

Descripción
In many practical scenarios, including those dealing with large data sets, calculating global estimators of unknown variables of interest becomes unfeasible. A common solution is obtaining partial estimators and combining them to approximate the global one. In this technical report, we focus on minimum mean squared error (MMSE) estimators, introducing two efficient linear schemes for the fusion of partial estimators. The proposed approaches are valid for any type of partial estimators, although in the simulated scenarios we concentrate on the combination of Monte Carlo estimators due to the nature of the problem addressed. Numerical results show the good performance of the novel fusion methods with only a fraction of the cost of the asymptotically optimal solution.
Internacional	Si
Entidad
Lugar
Páginas
Referencia/URL	http://vixra.org/abs/1410.0035
Tipo de publicación	Informe Técnico en viXra

Esta actividad pertenece a memorias de investigación

• Autor: David Luengo Garcia (UPM)

• Creador: Grupo de Investigación: Teoría de Aproximación Constructiva y Aplicaciones
• Departamento: Teoría de la Señal y Comunicaciones (Provisional)